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Differences between Security AI Chatbots and Dropzone AI Agents

Edward Wu
April 22, 2024

The rise of AI chatbots in cybersecurity has been primarily driven by the rapid advancements in Generative AI (Gen AI) and Large Language Models (LLMs). As a result, we now have a multitude of AI-powered security chatbots, such as  Microsoft Security CoPilot, CrowdStrike’s Charlotte, and SentinelOne’s Purple. Then, there is another Generative AI-powered system that is far more advanced than security chatbots called autonomous AI agents. Dropzone’s security AI agent is one such autonomous AI system. The variety of solutions available in the market can make it challenging to grasp the differences, navigate through the noise, and identify the right one that can best meet your needs. This article provides a detailed comparison between security chatbots and Dropzone security AI agents, helping you choose the best technology for your specific needs. 

While both technologies leverage the latest advances in Gen AI and  LLMs and enhance information accessibility and efficiency, they have critical differences. An excellent analogy to explain the difference between the two technologies is that of the conventional cruise control of a car vs. self-driving cars. Security chatbots are similar to conventional cruise control technology - where active driver input is required, such as accelerating and braking, changing lanes, watching traffic, etc., to reach the destination safely. Security AI agents are akin to self-driving cars, a level 4 autonomous driving solution requiring minimal human interaction and getting you to your destination autonomously and safely.

What are security chatbots, and how do they help security teams?

Security chatbots are AI-based virtual assistants that sit on top of existing security products and are programmed to help users with various security-related tasks through a chat-based, natural language interface similar to ChatGPT. So, instead of using a graphical user interface to interact with security products, users can ask questions in a conversational manner and get information or complete tasks like script analysis, creating risk summaries, threat hunting, and more. Since AI can assimilate and analyze vast amounts of data and generate insights at compute speed, they can accomplish these tasks much faster than humans. In summary, chatbots enhance the accessibility of information and save time for security teams in triaging security events and incidents. 

Where do security chatbots fall short?

While security chatbots offer many benefits, they have two major drawbacks. 

1. Continual human input to drive outcomes

Like cruise control driving, security chatbots need a full-time expert human analyst’s supervision and input a.k.a. prompting, to determine the output of security investigations. When working with a chatbot, analysts must know what to ask via prompts, ask specific questions to receive answers, and then ask follow-up questions based on the responses. This process can also be compared to a coin-operated machine, where every time you want to make progress, you need a good array of coins and insert the right coin or, in this case, ask another question. Essentially, the analyst must hand-hold the chatbot to get the desired results.

2. Complex orchestration between security chatbots

One major issue with security chatbots today is that they are usually developed by security vendors for their specific products and use cases, putting them at risk of lacking vendor neutrality. Additionally, since chatbots from different security vendors are not integrated, they cannot communicate with each other. This makes it cumbersome for security teams who have to work with multiple chatbots to complete their tasks. Let's take alert investigations, for example. For every alert investigation, the orchestration steps will involve the following:

  • Identify what information is needed to investigate the alert
  • Identify the security products that can provide the required information
  • Plan the questions that should be presented to different chatbots (i.e. chatbot matching)
  • Log into various security portals and ask different chatbots relevant questions
  • Wait for the responses from each chatbot
  • Aggregate information from each chatbot  
  • Complete the analysis external to these systems

The end result with security chatbots: modest efficiency gains

Security chatbots are significantly bottlenecked by the need for precise human input and hand-holding and implementation challenges. Therefore, chatbots may not be the best fit when you must get things done with limited time and effort. 

Understanding Dropzone Security AI agents

Security AI agents offer a higher level of automation than security chatbots. These are AI systems that replicate human behavioral characteristics, can autonomously plan and orchestrate analysis, draw conclusions, make decisions, and perform actions with minimal human intervention. 

Dropzone AI security agents, in particular, are designed to function as AI Tier 1 analysts and can ask questions on their own, decompose tasks, and check their own work. Similar to self-driving cars, Dropzone AI leverages the power of pre-trained AI security agents to perform autonomous alert investigations. The AI agents replicate expert human analysts’ decision-making process, understand your team and company’s context, and adapt to an ever-changing threat landscape to thoroughly and autonomously investigate all security alerts. No coding and no playbook execution are needed.

Dropzone security AI agent’s difference

100% autonomous investigations with no human intervention

Integrating seamlessly with existing security tools, Dropzone security AI agents pick up the alert the instant it is triggered, even before a human analyst needs to intervene. The agent swivel-chairs across different data sources such as network, SIEM, EDR logs, threat intelligence, and more, conducts inquiries with related parties, collects additional context, and performs a thorough analysis to conclude if an event is a false positive or a genuine threat. Once completed, it generates a comprehensive report for human analysts to review, with the conclusion, step-by-step process, and critical factors used to arrive at the conclusion. Ultimately, it aims to achieve the same input and output as a human Tier 1 analyst but without requiring constant human involvement. The final report includes a detailed backup for the conclusion. 

Vendor-agnostic system that works across security platforms

Unlike security chatbots, Dropzone AI agents offer a higher-level abstraction that works across multiple security and data products and vendors. They are vendor-agnostic and understand all types of data formats, so human analysts need not be experts in every security tool. 

The end result with Dropzone security AI agents: Up to 90% reduction in end-to-end investigation time

The higher level of automation and ability to traverse multiple products significantly reduces end-to-end investigation time by up to 90% and dramatically shortens Mean Time to Respond (MTTR). Such meaningful efficiency gains in investigations and MTTR reductions are more incremental (10% or less) with security chatbots. 

Choosing between Dropzone security AI agent vs. a security chatbot

Dropzone security AI agents are best used when a company is constrained by the realities of under-resourced and over-committed security teams facing increasing cyber risk. Suppose your organization has only a few security analysts (for example, three or fewer), and you are experiencing challenges with alert coverage, Dropzone AI is a great choice. Dropzone AI agents can significantly augment your team, increase your investigation intelligence bandwidth, and help effectively manage cyber risk. However, if you are an organization with hundreds of security analysts, have no coverage issues, and use Microsoft, SentinelOne, or CrowdStrike, then a chatbot may be useful as it still offers incremental efficiency gains. Ultimately, the choice between chatbots and AI agents will depend on a company's specific needs and the level of cyber risk they are dealing with.
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